Everpure launches data intelligence for AI projects

Everpure has launched Everpure Data Intelligence, a product aimed at helping companies prepare enterprise data for artificial intelligence use.

The launch is part of a broader push by the storage and data management company to move customers towards what it calls a data-centric architecture, with governance and context applied directly to information at source rather than through separate applications.

Everpure Data Intelligence is the renamed business from 1touch, which Everpure acquired earlier this year. The software is designed to discover, classify and contextualise data across on-premises systems, public clouds, software-as-a-service applications and third-party storage.

It is intended to address a problem many businesses say is slowing AI projects: fragmented data spread across multiple systems, with inconsistent controls and limited visibility. Everpure cited research from IDC and its own study showing that 45% of businesses are looking to implement a unified data platform to consolidate fragmented data environments for AI work.

Data bottleneck

Everpure said many enterprise IT estates still rely on application-led structures, where data and its meaning remain tied to separate business systems such as finance, logistics or sales. It argues that this model leads to duplication, operational blind spots and a lack of trusted information for AI systems.

The new offering has three main functions: universal discovery across structured and unstructured data, automated governance to identify sensitive information and track lineage, and what Everpure describes as AI-ready context through a semantic knowledge graph that links raw data to business definitions.

Charles Giancarlo, Chairman and CEO of Everpure, outlined the company’s position on that shift. “AI completely upends the traditional IT hierarchy; enterprises that do not shift from app-centricity to data primacy will fall behind,” said Giancarlo. “Because data is a company’s primary asset, embedding context, semantics and governance directly at the data layer is the right way to reduce data fragmentation created by the growth of apps and AI agents. Enterprises need to consolidate their fragmented enterprise data footprint into a real-time corpus of trusted intelligence.”

The software is available now. It works across data stored on the Everpure platform as well as external environments, reflecting the reality that many large businesses operate mixed estates rather than a single infrastructure stack.

Cloud and control

Alongside the launch, Everpure announced updates to its Enterprise Data Cloud architecture. These include changes to its Unified Data Plane and Intelligent Control Plane, intended to create a shared operating foundation across infrastructure and automate routine storage administration tasks.

One element is Evergreen//One Overdrive, a service due in the third quarter that is designed to provide temporary performance increases for on-premises storage during demand spikes of up to 25% above baseline, without requiring a permanent subscription change.

Other planned additions include workload rebalancing and mobility tools, natural-language workflow execution for storage administrators, enhanced cyber anomaly detection based on telemetry across the wider environment, and compliance monitoring intended to identify configuration drift.

Industry analysts have increasingly focused on data quality and governance as barriers to AI deployment, even as spending on chips and models continues to dominate headlines. Matt Kimball, VP and Principal Analyst at Moor Insights & Strategy, said many businesses are investing heavily in AI systems without resolving the underlying data issues.

“Enterprises are spending millions on advanced AI models and compute, but their underlying infrastructure is starving those systems with disconnected data,” said Kimball. “The biggest bottleneck to AI adoption right now isn’t the software, it’s the plumbing. Putting data at the absolute center of the enterprise strategy is exactly how IT leaders can rein in runaway operational costs and accelerate rollouts.”

Wider strategy

The announcement also reflects a wider effort by Everpure to move beyond storage hardware and position itself more firmly around data management, governance and automation. By embedding data discovery and policy controls into infrastructure workflows, the company is seeking to present a more integrated alternative to point tools used for classification, compliance and operational oversight.

For customers, the practical test will be whether the software can reduce the manual work involved in finding business-critical data, applying controls to sensitive records and making information usable for AI tools without broad replication across systems. Those issues have become more pressing as companies experiment with AI agents that need access to current, reliable enterprise data.

Everpure said the wider architecture is intended to show where data sits, how it connects and what it means across the estate, with governance rules attached to the data itself rather than enforced only through the application layer.